DATA2002 • Semester 2 • Manav Khemchandani
The Price of a Dream
Exploring what drives the cost of a dream house in the city of dreams.
Focus: Do bigger houses and lots actually mean higher prices?
Focus: Does having more amenities or newer construction raise house prices?
Focus: Do neighbourhood and environmental factors matter?
Focus: Do older homes lose value, and does heating/cooling system influence price?
:::::
:::
Box plot on amenities
Linear Regression results:
Box plot on Number of Rooms and Newly Constructed or not
Linear Regression results:
Multivariable linear regression: How does the price differ when all variables are combined?
Log-linear regression: Are there any outliers?
T-tests show a significant waterfront premium
Regression confirms Pct.College is a strong positive predictor of price
ANOVA shows Public sewer systems linked to higher prices
Combined regression: all three remain independent and significant
Bottom Summary: Neighbourhood quality and infrastructure are systematically capitalised into housing prices.
Figure 1: Correlation Matrix of each pair of variables
Figure 2: Assumptions plots before and after log transformation
Log-Adjusted Model: R-squared: ~
Simple Comparison Model: R-squared: ~
Interaction Model: R-squared: ~
Figure 3: Interactions Summary
Log-Adjusted VIF:
Living.Area Bathrooms
2.067436 2.067436
DATA2002 • Semester 2 • GROUP L21G03